"Multi-class Classification using SVM"

For this I want to use 2 SVM one trained on positive & not positive data & the other on negative & not negative data. Now I want to take the data predicted as positive by the 1st classifier & not negative by the second classifier as positive & data predicted as negative by the 2nd classifier & not positive by the 1st classifier as negative. In rest of the cases I want to tag the data as neutral.

I am very new to rapidminer. Can u plez explain a bit more? I am not able to put the 2 classiifers under the same root process. Can you please tell how can I put the 2 classifers under the same root process?

that depends very much on how your data looks like and what you want to achieve. A general approach would be the following:

- Use an AttributeConstruction to generate "isPositiv" and "isNegative" binary attribute- Declare the first as a label (ChangeAttributeRole)- Train a model- Set the second as a label- Train another model- Then, apply both models subsequently to the test set, and perform the inverse attribute construction on the two prediction attributes you get.